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The effectiveness of control measures during the 2022 COVID-19 outbreak in Shanghai, China

BACKGROUND: In March 2022, the Omicron variant of SARS-CoV-2 spread rapidly in Shanghai, China. The city adopted strict non-pharmacological intervention (NPI) measures, including lockdown (implemented on March 28 in Pudong and April 1 in Puxi) and blanket PCR testing (April 4). This study aims to un...

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Autores principales: Hu, Liangjian, Shi, Meisong, Li, Meili, Ma, Junling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10194905/
https://www.ncbi.nlm.nih.gov/pubmed/37200400
http://dx.doi.org/10.1371/journal.pone.0285937
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author Hu, Liangjian
Shi, Meisong
Li, Meili
Ma, Junling
author_facet Hu, Liangjian
Shi, Meisong
Li, Meili
Ma, Junling
author_sort Hu, Liangjian
collection PubMed
description BACKGROUND: In March 2022, the Omicron variant of SARS-CoV-2 spread rapidly in Shanghai, China. The city adopted strict non-pharmacological intervention (NPI) measures, including lockdown (implemented on March 28 in Pudong and April 1 in Puxi) and blanket PCR testing (April 4). This study aims to understand the effect of these measures. METHODS: We tabulated daily case counts from official reports and fitted a two-patch stochastic SEIR model to the data for the period of March 19 to April 21. This model considered two regions in Shanghai, namely Pudong and Puxi, as the implementation of control measures in Shanghai was carried out on different dates in these regions. We verified our fitting results using the data from April 22 to June 26. Finally, we applied the point estimate of parameter values to simulate our model while varying the dates of control measure implementation, and studied the effectiveness of the control measures. RESULTS: Our point estimate for the parameter values yields expected case counts that agree well the data for both the periods from March 19 to April 21 and from April 22 to June 26. Lockdown did not significantly reduce the intra-region transmission rates. Only about 21% cases were reported. The underlying basic reproduction number R(0) was 1.7, and the control reproduction number with both lockdown and blanket PCR testing was 1.3. If both measures were implemented on March 19, only about 5.9% infections would be prevented. CONCLUSIONS: Through our analysis, we found that NPI measures implemented in Shanghai were not sufficient to reduce the reproduction number to below unity. Thus, earlier intervention only has limited effect on reducing cases. The outbreak dies out because of only 27% of the population were active in disease transmission, possibly due to a combination of vaccination and lockdown.
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spelling pubmed-101949052023-05-19 The effectiveness of control measures during the 2022 COVID-19 outbreak in Shanghai, China Hu, Liangjian Shi, Meisong Li, Meili Ma, Junling PLoS One Research Article BACKGROUND: In March 2022, the Omicron variant of SARS-CoV-2 spread rapidly in Shanghai, China. The city adopted strict non-pharmacological intervention (NPI) measures, including lockdown (implemented on March 28 in Pudong and April 1 in Puxi) and blanket PCR testing (April 4). This study aims to understand the effect of these measures. METHODS: We tabulated daily case counts from official reports and fitted a two-patch stochastic SEIR model to the data for the period of March 19 to April 21. This model considered two regions in Shanghai, namely Pudong and Puxi, as the implementation of control measures in Shanghai was carried out on different dates in these regions. We verified our fitting results using the data from April 22 to June 26. Finally, we applied the point estimate of parameter values to simulate our model while varying the dates of control measure implementation, and studied the effectiveness of the control measures. RESULTS: Our point estimate for the parameter values yields expected case counts that agree well the data for both the periods from March 19 to April 21 and from April 22 to June 26. Lockdown did not significantly reduce the intra-region transmission rates. Only about 21% cases were reported. The underlying basic reproduction number R(0) was 1.7, and the control reproduction number with both lockdown and blanket PCR testing was 1.3. If both measures were implemented on March 19, only about 5.9% infections would be prevented. CONCLUSIONS: Through our analysis, we found that NPI measures implemented in Shanghai were not sufficient to reduce the reproduction number to below unity. Thus, earlier intervention only has limited effect on reducing cases. The outbreak dies out because of only 27% of the population were active in disease transmission, possibly due to a combination of vaccination and lockdown. Public Library of Science 2023-05-18 /pmc/articles/PMC10194905/ /pubmed/37200400 http://dx.doi.org/10.1371/journal.pone.0285937 Text en © 2023 Hu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hu, Liangjian
Shi, Meisong
Li, Meili
Ma, Junling
The effectiveness of control measures during the 2022 COVID-19 outbreak in Shanghai, China
title The effectiveness of control measures during the 2022 COVID-19 outbreak in Shanghai, China
title_full The effectiveness of control measures during the 2022 COVID-19 outbreak in Shanghai, China
title_fullStr The effectiveness of control measures during the 2022 COVID-19 outbreak in Shanghai, China
title_full_unstemmed The effectiveness of control measures during the 2022 COVID-19 outbreak in Shanghai, China
title_short The effectiveness of control measures during the 2022 COVID-19 outbreak in Shanghai, China
title_sort effectiveness of control measures during the 2022 covid-19 outbreak in shanghai, china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10194905/
https://www.ncbi.nlm.nih.gov/pubmed/37200400
http://dx.doi.org/10.1371/journal.pone.0285937
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